--- title: "Meta: Llama 3.1 8B Instruct — price, capability and what beats it · Undominated.ai" canonical: https://undominated.ai/models/meta-llama__llama-3.1-8b-instruct/ description: "Meta: Llama 3.1 8B Instruct: $0.020/M in, $0.040/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements." --- # Meta: Llama 3.1 8B Instruct — price, capability and what beats it · Undominated.ai > Meta: Llama 3.1 8B Instruct: $0.020/M in, $0.040/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements. [Check base rates for this workload](/check/meta-llama__llama-3.1-8b-instruct/) [Cheaper alternatives](/alternatives/meta-llama__llama-3.1-8b-instruct/) [Family](/families/llama/) [Compare models](https://undominated.ai/compare/?models=meta-llama%2Fllama-3.1-8b-instruct) Comparison context Choose up to three standard models in Compare. Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls. MODEL PROOF # Llama 3.1 8B Instruct Meta · 23 Jul 2024 Balanced Summarise Chat Code gen Agentic FRONTIER ## Nothing is both better and cheaper under this workload. **$0.025** / 1M tokens Balanced · 3 tokens in per 1 out Serving precision differs between offers. Evidence as of 06 Oct 2026 [openrouter/models](https://openrouter.ai/api/v1/models) [LMArena · cc-by-4.0](https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset) Independent LMArena score 1,186.5 ± 4.1 · 49,605 votes Context window 131.07K Maximum output 117.96K Input modalities text Output modalities text Published input price $0.020 / 1M tokens Published output price $0.040 / 1M tokens Pricing kind fixed Inspect [complete billing conditions](#billing-details) and endpoint terms below. Price from DeepInfra: the cheapest offer that is serving, at standard delivery and at a declared precision that is not 4-bit (fp8), at its standard rate. The maker’s own precision is not known. Every price dimension · USD per million tokens | Input | $0.020 /M | | --- | --- | | Output | $0.040 /M | | Cached input | Unknown /M | | Cache write | Unknown /M | | Cache write 1h | Unknown /M | | Reasoning | Unknown /M | ### Who sells it The same weights, different shops. Cheapest is not like-for-like when serving precision differs. Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.220/M from CoreWeave. 5 provider offers · rates, limits and conditions Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test. | Seller | Input | Output | Precision | Uptime (1d) | | --- | --- | --- | --- | --- | | Seller DeepInfra deepinfra/fp8 Endpoint terms Cached input /M Unknown Context limit 131,072 tokens Output limit 16,384 tokens Tools Not listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.94% | Input $0.020 | Output $0.040 | Precision fp8 | Uptime (1d) 99.91% | | Seller Novita novita/fp8 Endpoint terms Cached input /M Unknown Context limit 16,384 tokens Output limit 14,745 tokens Tools Not listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.67% | Input $0.020 | Output $0.050 | Precision fp8 | Uptime (1d) 98.92% | | Seller Groq groq Endpoint terms Cached input /M $0.025 Context limit 131,072 tokens Output limit 117,964 tokens Tools Listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.96% | Input $0.050 | Output $0.080 | Precision undeclared | Uptime (1d) 99.67% | | Seller Cloudflare cloudflare/fp8 Endpoint terms Cached input /M Unknown Context limit 32,000 tokens Output limit 28,800 tokens Tools Not listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 100.00% | Input $0.152 | Output $0.287 | Precision fp8 | Uptime (1d) 99.26% | | Seller CoreWeave coreweave/bf16 Endpoint terms Cached input /M $0.220 Context limit 131,072 tokens Output limit 117,964 tokens Tools Listed by endpoint Reasoning Not listed by endpoint Promotional discount None reported Uptime · last 30 minutes 100.00% | Input $0.220 | Output $0.220 | Precision bf16 | Uptime (1d) 100.00% | ### Independent scores | LMArena Elo | 1186.5 default | | --- | --- | LMArena Elo under CC BY 4.0. Absence of another board is not a score of zero. ### Capability | Context window | 131K | | --- | --- | | Max output | 117K | | Input modes | text | | Tool use | yes | | Reasoning | no | | Knowledge cutoff | 2023-12-31 | | Open weights | Unknown | ### Provenance | Price source | [openrouter.ai](https://openrouter.ai/api/v1/models) | | --- | --- | | Fetched | 2026-10-06 | | Quality data | verified | Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to... ## Questions this page answers What does Llama 3.1 8B Instruct cost? $0.020/M in, $0.040/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription. Does Llama 3.1 8B Instruct have an independent quality score? Llama 3.1 8B Instruct has an LMArena score in this catalogue. What beats Llama 3.1 8B Instruct? Nothing is both better and cheaper than Llama 3.1 8B Instruct. Does this page use Artificial Analysis scores for Llama 3.1 8B Instruct? No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated. Is the cheapest Llama 3.1 8B Instruct endpoint the same product? Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.220/M from CoreWeave. MODEL MONUMENT ## Save or share this proof Download proof card · 1200 × 630 Preview and more sharing options Meta: Llama 3.1 8B Instruct. Balanced workload. Frontier. Evidence as of 06 Oct 2026. Copy model link Download square card · 1080 × 1080 Copy landscape image Share landscape card ## Related - Side by side [gpt-oss-20b](/compare/meta-llama__llama-3.1-8b-instruct--vs--openai__gpt-oss-20b/) - Nearby on the capability axis [Command R (08-2024)](/models/cohere__command-r-08-2024/) - Same vendor [Llama 3.1 70B Instruct](/models/meta-llama__llama-3.1-70b-instruct/) - Meta models [Meta](/providers/meta/) - Where this model appears [frontier](/frontier/) - Nearby on the capability axis [Llama 3.2 3B Instruct](/models/meta-llama__llama-3.2-3b-instruct/) - Same vendor [Llama 3.3 70B Instruct](/models/meta-llama__llama-3.3-70b-instruct/) - Where this model appears [knee](/knee/) - Nearby on the capability axis [Phi 4](/models/microsoft__phi-4/) - Same vendor [Llama 3.2 1B Instruct](/models/meta-llama__llama-3.2-1b-instruct/) - Where this model appears [wire](/wire/) - Where this model appears [spreads](/spreads/) ## Badge The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not. Markdown Copy [![Llama 3.1 8B Instruct — Undominated.ai dominance verdict](https://undominated.ai/badge/meta-llama__llama-3.1-8b-instruct.svg)](https://undominated.ai/models/meta-llama__llama-3.1-8b-instruct/) HTML Copy Llama 3.1 8B Instruct — Undominated.ai dominance verdict Direct file: [https://undominated.ai/badge/meta-llama__llama-3.1-8b-instruct.svg](https://undominated.ai/badge/meta-llama__llama-3.1-8b-instruct.svg) — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never older than the last deploy. ## Continue your investigation - [Explore model families](/families/) - [Compare a shortlist](/compare/) - [Check a model](/check/) - [Understand the evidence](/methodology/)